All these are big data problems and the algorithims are themselves simple enough. It is not really inteligence except to the extent of memorizing a billion line items and then searching away. That is why it overwelmed chess and ultimately go as well. So now we are doing the same with driving and it should work out.
It does look like we are close and once there, it will take over all driving leaving the human as a trained observer for now.
Get over it folks. i want this applied to our six point drone craft so we can scoot about safely in three dimensions.
Of course, no one ever played a chess program to failure either.
AI Have Years of Failure then Stunning Success
April 8, 2024 by Brian Wang
There are many who believe that years of failure or limited success for Tesla FSD and other robotaxi projects are evidence for their belief that it will take more years from today for Tesla FSD to achieve robotaxi level.
Chess Computer Programs
In 1978 a chess engine named Belle won the North American Computer Chess Championship run by the Association for Computing Machinery, the engine’s special hardware allowed it to analyze around thirty million positions in three minutes. Belle also held both opening and ending database’s, greatly aiding the hardware speed. In 1980, Belle became to first chess engine to receive a Master rating.
In 1995, a new chess engine prototype was released from the team at IBM, Deep Blue. In 1996, Deep Blue faced chess champion Garry Kasparov for the first time. Kasparov won the six-game match by the score 4–2. In 1997, Deep Blue beat Garry Kasparov.
History of Computer Go
From 1971 to 2003, the Computer Go programs could barely play and would lose badly to human amateurs despite the Computers getting large handicaps.
Competitive Without Handicap with a Good Amateur
There was significant improvement from 2004 to 2014. In 2014, the software Crazy Stone and eleven-times German Go champion Franz-Jozef Dickhut, 6 dan amateur, played without a handicap. Dickhut won as was expected by most observers and himself before the match. However Crazy Stone won the first game by 1.5 points, which was a resounding mark that the top programs have reached top amateur level. In 2015, Dickhut won again 3-1 with computer program Zen winning the first game, again by 1.5 points.
Deep Mind Beat National and Then World Champions 2016-2017
In January 2016 both Facebook and Google DeepMind publish papers about their programs. DeepMind reports that AlphaGo beat the European Champion and Chinese professional Fan Hui by five games to none in an even game match, which took place in October 2015. A first for a computer program.
In March 2016 AlphaGo beats the top 9 dan Korean professional Lee Sedol 4:1 in a five game match in Seoul to world-wide publicity.
January 2017 provides another land-mark, with AlphaGo playing anonymously as Master on several Oriental servers against the very top professionals scoring a resounding 60 wins and no defeats, albeit with short time-limits. So there is no longer any doubt that computers can now play Go better than humans.
March 2017 provided a final match for AlphaGo Master, being retired from competition after beating the acknowledged world’s best player, the Chinese Ke Jie, 3-0.
In October 2017 it was announced that AlphaGo Zero, armed with just the rules, had in 40 days become even better at Go than the original AlphaGo, without the help of game records.
Robotaxi
In October 2018, the California Department of Motor Vehicles issued a permit for Waymo to operate cars without safety drivers. There have been other permits for robotaxi with no safety drivers in the US and China for companies like Waymo, Cruise and Apollo. In 2022, Baidu’s Apollo Go and Pony.ai received permission from Beijing city to remove the safety driver for part of their robotaxi business in a suburb. Cruise has since suspended service. These robotaxi services all used extensive LIDAR (laser radar) and hypermapping for small regions to offer limited services with at most a few hundred vehicles.
Tesla FSD Progress
Tesla has made large progress with its full self driving system. In late 2022, it has gone to end to end neural networks. It is training directly from video. The Tesla FSD 12.X are nearing feature complete and are being assessed as providing human-like driving. Tesla is using far more compute and training data than the equivalent neural net Go program. The shocking completion of the Go programs from 2015 to 2016 is what could be possible. The 2016 equivalent of being competitive with Grandmasters in Go would be a sufficient standard for super high quality Tesla FSD.
Tesla has opened up the service for one month free trials for all Tesla owners in the USA. This usage by 2.5 million drivers will increase the FSD training driving miles from 1 billion to over 2 billion miles. High rates of usage of a quality system will add 0.5 to 2 billion driving miles every month when the system is rolled out in the USA, Canada and China.
No comments:
Post a Comment